Result for 8F6238F616E80B3A78ABD04C261272F5E5FC760B

Query result

Key Value
FileName./usr/share/doc/libghc-hierarchical-clustering-doc/html/src/Data-Clustering-Hierarchical-Internal-Types.html
FileSize14478
MD5E0F71D3F8C56CD590CA9C647B5F51215
SHA-18F6238F616E80B3A78ABD04C261272F5E5FC760B
SHA-256BE6E4AAD989FC11CE8CFC4D9507FE38603CCCB5156A9DC5E089A0F0525EA984D
SSDEEP384:mbOL+fNPY10cMBi12t1JaSoj8oXJTfX5fUU5jcvSnWavg4m:qNnC2XJa3jFXJjXxUUtoSW2tm
TLSHT14552BCD0C2F38A262132D0E3658E3FF2B4E004EDD6DA5668A2EF477657AED14BC57814
hashlookup:parent-total3
hashlookup:trust65

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Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize46806
MD5DD692E51CD48BA557DDE4D603FFCCD64
PackageDescriptionfast algorithms for single, average/UPGMA and complete linkage clustering; documentation This package provides a function to create a dendrogram from a list of items and a distance function between them. Initially a singleton cluster is created for each item, and then new, bigger clusters are created by merging the two clusters with least distance between them. The distance between two clusters is calculated according to the linkage type. The dendrogram represents not only the clusters but also the order on which they were created. . This package has many implementations with different performance characteristics. There are SLINK and CLINK algorithm implementations that are optimal in both space and time. There are also naive implementations using a distance matrix. Using the dendrogram function from Data.Clustering.Hierarchical automatically chooses the best implementation we have. . This package provides the documentation for a library for the Haskell programming language. See http://www.haskell.org/ for more information on Haskell.
PackageMaintainerDebian Haskell Group <pkg-haskell-maintainers@lists.alioth.debian.org>
PackageNamelibghc-hierarchical-clustering-doc
PackageSectiondoc
PackageVersion0.4.6-3
SHA-1FF3242B7D68395F22BA6C69AF9B50CE0B53367B7
SHA-2565C4E1CA3A94D7B0E6C3856AF6FAEC9DC9EBCEE2C0A4FDCDFDFF065B5B835DFDA
Key Value
FileSize32672
MD5BF8FF2B26616380BC7F58F6118C147D2
PackageDescriptionFast algorithms for single, average/UPGMA and complete linkage clustering.; documentation This package provides a function to create a dendrogram from a list of items and a distance function between them. Initially a singleton cluster is created for each item, and then new, bigger clusters are created by merging the two clusters with least distance between them. The distance between two clusters is calculated according to the linkage type. The dendrogram represents not only the clusters but also the order on which they were created. . This package has many implementations with different performance characteristics. There are SLINK and CLINK algorithm implementations that are optimal in both space and time. There are also naive implementations using a distance matrix. Using the dendrogram function from Data.Clustering.Hierarchical automatically chooses the best implementation we have. . This package provides the documentation for a library for the Haskell programming language. See http://www.haskell.org/ for more information on Haskell.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamelibghc-hierarchical-clustering-doc
PackageSectiondoc
PackageVersion0.4.6-1
SHA-11EAD772B83525DFAB1E16EE5E973447D2244E894
SHA-25606DE225AEFB0668DD474255F72F2282D7D6B62598FD8D50E8C8A0B05462C00AA
Key Value
FileSize34228
MD5A835A9D23E198B5B3B777570233D966C
PackageDescriptionfast algorithms for single, average/UPGMA and complete linkage clustering; documentation This package provides a function to create a dendrogram from a list of items and a distance function between them. Initially a singleton cluster is created for each item, and then new, bigger clusters are created by merging the two clusters with least distance between them. The distance between two clusters is calculated according to the linkage type. The dendrogram represents not only the clusters but also the order on which they were created. . This package has many implementations with different performance characteristics. There are SLINK and CLINK algorithm implementations that are optimal in both space and time. There are also naive implementations using a distance matrix. Using the dendrogram function from Data.Clustering.Hierarchical automatically chooses the best implementation we have. . This package provides the documentation for a library for the Haskell programming language. See http://www.haskell.org/ for more information on Haskell.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamelibghc-hierarchical-clustering-doc
PackageSectiondoc
PackageVersion0.4.6-3build1
SHA-16B1631D6F0CF6D4FF0F3C9DDD43F9E937AC50AF0
SHA-256ECBBC054C285C2F922DBF7D0C9D3E347A48F67337693A8C4099254F3BAB0D4A5